3,647 research outputs found

    On the Parikh-de-Bruijn grid

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    We introduce the Parikh-de-Bruijn grid, a graph whose vertices are fixed-order Parikh vectors, and whose edges are given by a simple shift operation. This graph gives structural insight into the nature of sets of Parikh vectors as well as that of the Parikh set of a given string. We show its utility by proving some results on Parikh-de-Bruijn strings, the abelian analog of de-Bruijn sequences.Comment: 18 pages, 3 figures, 1 tabl

    Inferring an Indeterminate String from a Prefix Graph

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    An \itbf{indeterminate string} (or, more simply, just a \itbf{string}) \s{x} = \s{x}[1..n] on an alphabet Σ\Sigma is a sequence of nonempty subsets of Σ\Sigma. We say that \s{x}[i_1] and \s{x}[i_2] \itbf{match} (written \s{x}[i_1] \match \s{x}[i_2]) if and only if \s{x}[i_1] \cap \s{x}[i_2] \ne \emptyset. A \itbf{feasible array} is an array \s{y} = \s{y}[1..n] of integers such that \s{y}[1] = n and for every i2..ni \in 2..n, \s{y}[i] \in 0..n\- i\+ 1. A \itbf{prefix table} of a string \s{x} is an array \s{\pi} = \s{\pi}[1..n] of integers such that, for every i1..ni \in 1..n, \s{\pi}[i] = j if and only if \s{x}[i..i\+ j\- 1] is the longest substring at position ii of \s{x} that matches a prefix of \s{x}. It is known from \cite{CRSW13} that every feasible array is a prefix table of some indetermintate string. A \itbf{prefix graph} \mathcal{P} = \mathcal{P}_{\s{y}} is a labelled simple graph whose structure is determined by a feasible array \s{y}. In this paper we show, given a feasible array \s{y}, how to use \mathcal{P}_{\s{y}} to construct a lexicographically least indeterminate string on a minimum alphabet whose prefix table \s{\pi} = \s{y}.Comment: 13 pages, 1 figur

    Computing Covers Using Prefix Tables

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    An \emph{indeterminate string} x=x[1..n]x = x[1..n] on an alphabet Σ\Sigma is a sequence of nonempty subsets of Σ\Sigma; xx is said to be \emph{regular} if every subset is of size one. A proper substring uu of regular xx is said to be a \emph{cover} of xx iff for every i1..ni \in 1..n, an occurrence of uu in xx includes x[i]x[i]. The \emph{cover array} γ=γ[1..n]\gamma = \gamma[1..n] of xx is an integer array such that γ[i]\gamma[i] is the longest cover of x[1..i]x[1..i]. Fifteen years ago a complex, though nevertheless linear-time, algorithm was proposed to compute the cover array of regular xx based on prior computation of the border array of xx. In this paper we first describe a linear-time algorithm to compute the cover array of regular string xx based on the prefix table of xx. We then extend this result to indeterminate strings.Comment: 14 pages, 1 figur

    String Comparison in VV-Order: New Lexicographic Properties & On-line Applications

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    VV-order is a global order on strings related to Unique Maximal Factorization Families (UMFFs), which are themselves generalizations of Lyndon words. VV-order has recently been proposed as an alternative to lexicographical order in the computation of suffix arrays and in the suffix-sorting induced by the Burrows-Wheeler transform. Efficient VV-ordering of strings thus becomes a matter of considerable interest. In this paper we present new and surprising results on VV-order in strings, then go on to explore the algorithmic consequences

    Lyndon Array Construction during Burrows-Wheeler Inversion

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    In this paper we present an algorithm to compute the Lyndon array of a string TT of length nn as a byproduct of the inversion of the Burrows-Wheeler transform of TT. Our algorithm runs in linear time using only a stack in addition to the data structures used for Burrows-Wheeler inversion. We compare our algorithm with two other linear-time algorithms for Lyndon array construction and show that computing the Burrows-Wheeler transform and then constructing the Lyndon array is competitive compared to the known approaches. We also propose a new balanced parenthesis representation for the Lyndon array that uses 2n+o(n)2n+o(n) bits of space and supports constant time access. This representation can be built in linear time using O(n)O(n) words of space, or in O(nlogn/loglogn)O(n\log n/\log\log n) time using asymptotically the same space as TT

    String Covering: A Survey

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    The study of strings is an important combinatorial field that precedes the digital computer. Strings can be very long, trillions of letters, so it is important to find compact representations. Here we first survey various forms of one potential compaction methodology, the cover of a given string x, initially proposed in a simple form in 1990, but increasingly of interest as more sophisticated variants have been discovered. We then consider covering by a seed; that is, a cover of a superstring of x. We conclude with many proposals for research directions that could make significant contributions to string processing in future

    Algorithms to Compute the Lyndon Array

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    We first describe three algorithms for computing the Lyndon array that have been suggested in the literature, but for which no structured exposition has been given. Two of these algorithms execute in quadratic time in the worst case, the third achieves linear time, but at the expense of prior computation of both the suffix array and the inverse suffix array of x. We then go on to describe two variants of a new algorithm that avoids prior computation of global data structures and executes in worst-case n log n time. Experimental evidence suggests that all but one of these five algorithms require only linear execution time in practice, with the two new algorithms faster by a small factor. We conjecture that there exists a fast and worst-case linear-time algorithm to compute the Lyndon array that is also elementary (making no use of global data structures such as the suffix array)

    Numerical shock propagation using geometrical shock dynamics

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    A simple numerical scheme for the calculation of the motion of shock waves in gases based on Whitham's theory of geometrical shock dynamics is developed. This scheme is used to study the propagation of shock waves along walls and in channels and the self-focusing of initially curved shockfronts. The numerical results are compared with exact and numerical solutions of the geometrical-shock-dynamics equations and with recent experimental investigations
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